Strategic Intelligence: Physical AI

Strategic Intelligence: Physical AI

Summary

Physical AI is the next step in the evolution of robotics. It marks a shift from machines that follow fixed instructions to embodied systems that perceive, reason, and act autonomously. Physical AI systems are built on real-world physical interaction data, incorporate an understanding of the physical world, and are deployed in physical entities such as robots, autonomous vehicles, drones, or industrial systems.

Key Highlights

• Physical AI combines multiple technologies, including the Internet of Things (IoT), generative AI, agentic AI, machine learning, world models, vision-language models (VLMs), and vision-language action (VLA) models. Physical AI uses multimodal tools (like VLMs) to interpret sensory data, understand spatial relationships, and plan complex sequences of actions to achieve a goal.
• Early industry adopters of physical AI include discrete manufacturing, healthcare, security and surveillance, mining, energy, construction, and transportation. In Asia Pacific (APAC), physical AI deployments are underway to address labor shortages, especially in the manufacturing sector.

Scope

• This report provides an overview of physical AI, which is the next step in the evolution of robotics.
• It provides a clear definition of physical AI and analyzes the theme's value chain.
• The report gives an overview of geographic trends in physical AI, with a focus on Chjna, Japan, and South Korea, and includes details of industry case studies.

Reasons to Buy

• Early commercialization of physical AI is occurring across numerous industries. The real acceleration from 2027 onward will be driven by dramatic drops in the cost of dexterous actuation and edge-computing hardware, and the maturation of large language models (LLMs) that enable general-purpose reasoning, real-world navigation, and task learning without hours of programming. This report provides an invaluable insight into this highly disruptive and fast-moving theme.